Psychiatry

Global evolution of adolescent idiopathic scoliosis research (1990-2025): a bibliometric and visualization analysis.

PURPOSE: Adolescent idiopathic scoliosis (AIS) is the most common spinal deformity affecting adolescents, yet comprehensive analysis of global research trends remains limited. This study aims to identify research hotspots, collaboration patterns, and emerging frontiers to guide future research priorities. METHODS: Publications on AIS from 1990 to October 2025 were retrieved from the Web of Science...

Rapid glycomic analysis of serum EVs reveals altered N-glycosylation patterns in ASD.

Objective laboratory diagnostics for autism spectrum disorder (ASD) are lacking, necessitating rapid clinical screening tools. Because serum extracellular vesicle (EV) N-glycosylation captures critical neurodevelopmental signatures, we developed a fast, biologically interpretable diagnostic strategy. EVs from ASD patients with language impairment and neurotypical controls were isolated using a rap...

Transdiagnostic monoamine-based subtyping for attention-deficit/hyperactivity disorder and autism spectrum disorder via unsupervised machine learning.

Neuroimaging and molecular studies have examined the etiology of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). H...

An overview of current and emerging strategies for phantom limb pain.

INTRODUCTION: Phantom limb pain (PLP) is a disabling neuropathic pain syndrome affecting many individuals following limb amputation. Despite decades o...

Machine learning reveals a multimodal, transdiagnostic signature of emotion dysregulation vulnerability across patients, offspring, and controls.

Emotion dysregulation (ED) is a core transdiagnostic feature of several psychiatric disorders, including borderline personality disorder, bipolar diso...

miR-124 Ameliorates Spatial Memory Deficits in Rats Exposed to Single-Prolonged Stress by Downregulating IQGAP1 to Regulate Actin-Binding Proteins and Apoptosis in Hippocampal Neurons.

Post-traumatic stress disorder (PTSD) is a highly prevalent, trauma-induced psychiatric condition characterized by persistent cognitive-affective dysf...

Retraction: Hybrid deep learning and feature selection approach for autism detection from rs-fMRI data.

Identifying cluster profiles based on barriers and facilitators to physical activity during COVID-19 confinement: A cross-sectional study using machine learning analysis.

Social restrictions, such as confinement periods, tend to reduce physical activity (PA) levels. However, sociodemographic factors may influence specif...

Imaging features of affective and non-affective psychosis.

Affective and non-affective psychoses exhibit heterogeneous clinical presentation, neurobiological underpinnings, and treatment response. This special...

Mapping Depression Correlated Amygdala Communication.

The amygdala is a central hub for emotional processing, whose interactions with large-scale brain networks have been implicated in the pathophysiology...

Harnessing Latent Dirichlet Allocation-based topic modeling to unveil the focus areas in Ayush healthcare in India.

The exponential growth of unstructured data has presented new opportunities for leveraging computational techniques to uncover meaningful insights in ...

Multimodal deep learning for detecting current depressive symptom status using wearable time-series data and structural brain MRI in high-risk occupational groups.

In high-risk occupational groups, current mental health status may be underreported because of stigma or concerns about disadvantage. Wearable data ca...

Predicting return-to-work outcomes: A comparative analysis of logistic regression and machine learning in occupational mental health.

This investigation compares the analytical performance of logistic regression (LR) and targeted maximum likelihood estimation (TMLE) methodologies for...

Perceived control influences users' acceptance of AI-enabled services.

With the rapid diffusion of artificial intelligence (AI) in the service sector, users' acceptance of AI-enabled services has become an important issue...

The Quality of Suicide-Related Stories Generated by Large Language Models.

Background: Suicide-related media is known to influence suicide rates. Large language models (LLMs), a form of generative artificial intelligence (AI)...

A Framework for Predicting Neurofeedback Treatment Response in ADHD Using EEG Functional Connectivity and Genetic Algorithm-Driven Channel Selection.

In this article, we present a computational framework for predicting treatment response to neurofeedback (NF) among patients with Attention-Deficit/Hy...

Multimodal Domain Generalization for Depression Detection: An Attention-Based BiLSTM Network With Domain-Adversarial Training.

Automatic depression detection with deep learning has shown promise, but often suffers from limited generalization due to domain shift arising from in...

A hybrid CNN-machine learning model for anxiety screening with mandala coloring patterns: Feature extraction and classification performance.

Traditional anxiety assessments typically rely on self-report questionnaires and often emphasize somatic symptoms, potentially overlooking nuanced beh...

AI awareness, AI fear of missing out, and work demotivation as pathways to occupational strain in Vietnamese hospitality employees.

Artificial intelligence (AI) is reshaping hospitality work and changing how employees perceive occupational risks and their capacity to adapt. How the...

Unmasking data leakage in EEG-ADHD literature: a rigorous, interpretable SOTA framework (DSAEN).

The field of translational Electroencephalogram-Artificial Intelligence (EEG-AI) faces a significant methodological challenge regarding epoch-wise dat...